| /* |
| * Copyright (c) 2022-2024 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| |
| #include "tests/AssetsLibrary.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/datasets/SmallConvolutionLayerDataset.h" |
| #include "tests/framework/datasets/Datasets.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/framework/Macros.h" |
| #include "tests/validation/fixtures/dynamic_fusion/gpu/cl/DirectConv2dFixture.h" |
| #include "tests/validation/reference/ConvolutionLayer.h" |
| #include "tests/validation/Validation.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| /** Tolerances from tests/validation/CL/DirectConvolutionLayer.cpp |
| */ |
| RelativeTolerance<float> tolerance_f32( |
| 0.05f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| RelativeTolerance<half_float::half> tolerance_f16(half_float::half( |
| 0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */ |
| constexpr float abs_tolerance_f32(0.0001f); /**< Absolute tolerance for FP32 tests*/ |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number */ |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(DYNAMIC_FUSION) |
| /** Synced with tests/validation/CL/ConvolutionLayer.cpp |
| * |
| * Difference | Why the difference |
| * f32 tolerance here is smaller | To use the same tolerance as that of DirectConv2d; lowering tolerance is safe |
| * No quantized tests | Not supported yet |
| * No grouped CNN tests | Not supported yet |
| * No mixed layout tests | Not needed; only NHWC is supported |
| * No activation | Not needed in fusion |
| * No ValidateConvolutionMethod | Only a single method (direct conv2d) is supported |
| * No ReshapeWeights = true tests | Not applicable yet. This parameter only concerns gemm-based conv2d |
| * No RunSmallWithPadding tests | Padding is removed |
| * |
| */ |
| TEST_SUITE(CONV2D) |
| |
| template <typename T> |
| using DynamicFusionGpuConv2dFixture = DynamicFusionGpuConv2dValidationFixture<CLTensor, CLAccessor, GpuConv2d, T>; |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, |
| DynamicFusionGpuConv2dFixture<float>, |
| framework::DatasetMode::ALL, |
| combine(combine(combine(datasets::SmallConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("DataLayout", {DataLayout::NHWC})), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo()))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f32); |
| } |
| TEST_SUITE_END() // FP32 |
| |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, |
| DynamicFusionGpuConv2dFixture<half>, |
| framework::DatasetMode::ALL, |
| combine(combine(combine(datasets::SmallConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("DataLayout", {DataLayout::NHWC})), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo()))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| TEST_SUITE_END() // FP16 |
| |
| // Tests for specific conv2d methods |
| /** Synced with tests/validation/CL/DirectConvolutionLayer.cpp |
| * |
| * Difference | Why the difference |
| * No quantized tests | Not supported yet |
| * No Invalid output size test | Not applicable. Output is removed from the interface |
| * No mixed layout/NCHW tests | Not needed; only NHWC is supported |
| * No activation tests | Not needed in fusion |
| */ |
| TEST_SUITE(DIRECT_CONV2D) |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid: Mismatching data type input/weights |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid: Mismatching input feature maps |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid weights dimensions |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Unsupported biases size |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Unsupported biases dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Unsupported data layout: NCHW |
| TensorInfo(TensorShape(2U, 32U, 16U), 1, DataType::QASYMM8, DataLayout::NHWC), // Unsupported data type: quantized |
| TensorInfo(TensorShape(2U, 32U, 16U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Arbitrary weight sizes for NHWC are supported |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Non-rectangular weights dimensions for NHWC are supported |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Strides > 2 for any kernel sizes for NHWC are supported |
| }), |
| framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F16, DataLayout::NHWC), |
| TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 3U, 3U, 4U, 3U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(2U, 1U, 1U, 4U), 1, DataType::QASYMM8, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 1U, 1U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 13U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 5U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| })), |
| framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(3U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U, 2U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(25U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(4U), 1, DataType::QASYMM8, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| })), |
| framework::dataset::make("Conv2dAttributes", { |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({1, 1}).pad({0, 0, 0, 0}), |
| Conv2dAttributes().stride({3, 3}).pad({0, 0, 0, 0}), |
| })), |
| framework::dataset::make("Expected", { false, false, false, false, false, false, false, true, true, true, true })), |
| input_info, weights_info, biases_info, conv2d_attrs, expected) |
| { |
| auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); |
| auto context = GpuWorkloadContext{ &cl_compile_ctx }; |
| GpuWorkloadSketch sketch{ &context }; |
| |
| const ITensorInfo* sketch_input_info = context.create_tensor_info(input_info); |
| const ITensorInfo* sketch_weights_info = context.create_tensor_info(weights_info); |
| const ITensorInfo* sketch_biases_info = context.create_tensor_info(biases_info); |
| bool is_valid = bool(GpuConv2d::validate_op(sketch, sketch_input_info, sketch_weights_info, sketch_biases_info, conv2d_attrs)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| template <typename T> |
| using DynamicFusionGpuDirectConv2dFixture = DynamicFusionDirectConv2dValidationFixture<CLTensor, CLAccessor, GpuConv2d, T>; |
| |
| TEST_SUITE(FP16) |
| /// TODO: COMPMID-6877: Once the issue in Conv2d is resolved, re-enable these |
| FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDirectConv2dFixture<half>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1, 3, 1, 1 })), |
| framework::dataset::make("StrideY", { 1, 3, 2, 1 })), |
| framework::dataset::make("PadX", { 1, 3, 0, 4 })), |
| framework::dataset::make("PadY", { 1, 3, 0, 4 })), |
| framework::dataset::make("KernelSize", { 3, 8, 1, 9 })), |
| framework::dataset::make("NumKernels", { 17, 3, 1, 19 })), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDirectConv2dFixture<half>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 9 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| |
| TEST_SUITE_END() // FP16 |
| |
| TEST_SUITE(FP32) |
| /// TODO: COMPMID-6877: Once the issue in Conv2d is resolved, re-enable these |
| FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDirectConv2dFixture<float>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1, 3, 1, 1 })), |
| framework::dataset::make("StrideY", { 1, 3, 2, 1 })), |
| framework::dataset::make("PadX", { 1, 3, 0, 4 })), |
| framework::dataset::make("PadY", { 1, 3, 0, 4 })), |
| framework::dataset::make("KernelSize", { 3, 8, 1, 9 })), |
| framework::dataset::make("NumKernels", { 17, 3, 1, 19 })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_f32, 0.0, abs_tolerance_f32); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDirectConv2dFixture<float>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 9 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_f32, 0.0, abs_tolerance_f32); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| TEST_SUITE_END() // FP32 |
| TEST_SUITE_END() // DIRECT_CONV2D |
| TEST_SUITE_END() // CONV2D |
| TEST_SUITE_END() // DYNAMIC_FUSION |
| TEST_SUITE_END() // CL |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |